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Title: Mining Sequential Patterns Across Multiple Sequence Databases
Authors: Liao, Zhung-Xun; Hu, Xing-Yuan; Peng, Wen-Chih
Keywords: no
Issue Date: 10-11-2008
Abstract: In reality, sequential patterns may exist in multiple sequence databases. In this paper, we explore a novel sequential pattern mining problem: mining multi-domain sequential patterns across multiple domain sequence databases. We propose two algorithms, IndividualMine and PropagatedMine, for efficiently mining multi-domain sequential patterns. In algorithm IndividualMine, sequential patterns in each domain should first be discovered and then by iteratively combining sequential patterns among domain sequence databases, multi-domain sequential patterns are generated. Algorithm PropagatedMine performs sequential pattern mining only in one domain sequence database and propagates sequential patterns mined to other domain to generate corresponding sequential patterns so as to reduce the cost of mining. A comprehensive performance study is conducted and experimental results show the scalability and the efficiency of our proposed algorithms.
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